Lead Bioinformatics Scientist, NGS

We’re seeking an experienced computational scientist to lead the design, development, and operation of the NGS analysis platform that powers Profluent’s gene editing and protein design programs. You’ll work at the intersection of computational biology, software engineering, and experimental biology to build scalable systems that extract clear, actionable insights from large-scale sequencing data.

In this role, you’ll architect core bioinformatics infrastructure, define analytical strategy, and collaborate closely with experimental and ML teams to accelerate design-build-test-learn cycles. You’ll also mentor team members, promote software engineering best practices, and help shape the future of Profluent’s computational biology capabilities.

• →Lead design and implementation of scalable NGS analysis pipelines supporting gene editing and protein engineering workflows
• →Develop clear, intuitive visualizations and reports to communicate sequencing results and biological insights
• →Manage cloud-based compute environments and data systems for large-scale datasets
• →Partner with biology teams to analyze results, troubleshoot, and optimize experimental design
• →Collaborate with machine learning teams to curate data for model training
• →Establish best practices for code review, testing, and CI/CD in computational workflows
• →Mentor junior scientists and foster a culture of rigor, reproducibility, and innovation

• PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
• 5+ years of experience analyzing NGS datasets (e.g., amplicon sequencing, high-throughput editing, or screening experiments)
• Strong programming skills in Python (pandas, numpy, biopython, etc.)
• Expertise with workflow orchestration tools (Nextflow, Snakemake) and cloud environments (GCP, AWS)
• Experience with containerization (Docker, Kubernetes) and scalable compute infrastructure
• Deep understanding of Linux, git-based version control, and software engineering best practices
• Proven ability to transform complex sequencing data into actionable biological insights

• Experience with gene editing technologies (CRISPR, base or prime editing; strongly preferred)
• Familiarity with SQL and data modeling for biological or experimental data
• Experience with LIMS platforms (e.g., Benchling) and lab data integration
• Track record of developing production-quality scientific software or open-source bioinformatics tools

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.